Balancing smartness and privacy for the Ambient Intelligence

Harold van Heerde (1, 2) , Nicolas Anciaux (2, 3) , Ling Feng (1) , Peter M. G. Apers (1)

1 University of Twente
2 SMIS - Secured and Mobile Information Systems
3 PRISM - Parallélisme, Réseaux, Systèmes, Modélisation

Ambient Intelligence (AmI) will introduce large privacy risks. Stored context histories are vulnerable for unauthorized disclosure, thus unlimited storing of privacy-sensitive context data is not desirable from the privacy viewpoint. However, high quality and quantity of data enable smartness for the AmI, while less and coarse data benefit privacy. This raises a very important problem to the AmI, that is, how to balance the smartness and privacy requirements in an ambient world. In this article, we propose to give to donors the control over the life cycle of their context data, so that users themselves can balance their needs and wishes in terms of smartness and privacy.

Domaines: Base de données [cs.DB]

Harold van Heerde, Nicolas Anciaux, Ling Feng, Peter M. G. Apers. Balancing smartness and privacy for the Ambient Intelligence. EuroSCC 2006 : European Conference on Smart Sensing and Context, Oct 2006, Enschede, Netherlands. pp.255-258, ⟨10.1007/11907503_26⟩. ⟨inria-00321682⟩